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Alternatives to cogmem

  • A
    license
    B
    quality
    D
    maintenance
    Local Markdown-backed memory tools for Codex and other MCP-capable agents. Exposes durable agent knowledge via CLI and MCP server.
    5
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    Hand a project over — to your next session, to Cursor/Codex/Gemini, to your successor — with the reasons attached. Local-first memory MCP for coding agents: decisions re-injected before the agent acts, drift detection across every project you run. One SQLite file, nothing leaves your machine.
    8
    87 npm
    15
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep
    5
    80 PyPI
    1
    MIT

Related Servers

  • A
    license
    A
    quality
    A
    maintenance
    Local-first memory layer for AI coding agents — captures issues, attempts, fixes, and decisions, and warns at git commit before you repeat a mistake.
    17
    238 PyPI
    866
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Local-first project memory for AI coding agents. Records failed attempts, fragile files, and decisions per repo, and warns the agent via hooks before it repeats a recorded mistake.
    6
    60 npm
    MIT
  • F
    license
    Not graded
    quality
    A
    maintenance
    Local-first memory for AI agents with evidence-backed recall, deterministic trust verdicts, self-inspection, and a tamper-evident audit history.
    3
    -
  • A
    license
    A
    quality
    A
    maintenance
    Local-first, code-aware engineering cognition for AI coding agents - persistent memory, contextual retrieval, and continuous cognition about your codebase.
    4
    15
    3
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    Provides a local-first memory layer for coding agents, storing principles, rules, and corrections on-device and surfacing them at the moments they apply so agents act on the intended outcomes without sending data to the cloud.
    13,776 npm
    2
    AGPL 3.0

TDQS

A4.6/5.0

Scored across 8 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: note saves memories, recall retrieves them, progress summarizes project state, receipt provides cryptographic proofs, review_pending lists pending rules, status reports system health, tree_head returns the Merkle root, and verify performs deep audit. No overlapping functionality.

Naming Consistency5/5

All tool names are lowercase with underscores for compounds (e.g., review_pending, tree_head). They follow a consistent pattern of verbs or noun phrases that clearly indicate the action or output, with no style mixing.

Tool Count5/5

With 8 tools, the set is well-scoped for a verifiable memory system. It covers storing, retrieving, verifying, and monitoring without being bloated or too sparse.

Completeness4/5

The tools provide core operations (create, read, verify, audit). Missing explicit update/delete tools is a minor gap, but this aligns with the system's append-only, tamper-evident design. A tool for exact-match retrieval could be useful, but semantic recall covers most needs.

Maintenance

ActivitySlowing
ResponsivenessResponsive